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The CalHealth Finger Blood Pressure Monitor, MDMouse is noninvasive blood pressure measurement systems intended to measure the systolic and diastolic blood pressures and pulse rate of an adult individual, over age 18, at home by using a non-invasive technique in which an inflatable cuff is wrapped around the left index finger. The cuff circumference is designed for Left Index Finger circumference: 1.5' ~ 3.5' (3.7~8.8 cm) for finger type.

CalHealth Finger Blood Pressure Monitor, MDMouse uses the Oscillometric method to measure the blood pressure. The Oscillometric method is adopted clinically to measure the blood pressure recently. It is not needed to use the stethoscope, as in the traditional measuring method, to monitor the Korotkov sound when deciding the systolic or diastolic pressure. The Oscillometric method senses the vibrating signal via the closed air pipe system and utilizes the microcomputer to automatically sense the characteristics of the pulse signal. Through simple calculation, the reading can reflect the accurate real blood pressure, and the systolic pressure is defined as the pressure when the cuff pressure oscillating amplitude begins to increase and the diastolic pressure as the pressure when the cuff pressure oscillating amplitude stops decreasing.

The provided 510(k) summary for the CalHealth, Inc. Finger Blood Pressure Monitor, MDMouse, focuses on demonstrating substantial equivalence to a predicate device rather than detailing specific acceptance criteria and a standalone study proving the device meets those criteria.

However, based on the information provided, we can infer some aspects and identify what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

The document mentions adherence to several standards related to safety, EMC, and performance. The "PASS" designation indicates the device met the requirements of these standards. While specific numerical acceptance criteria (e.g., accuracy ranges for blood pressure measurements) are not explicitly stated in the summary, they would be inherent to the AAMI / ANSI SP10 standard mentioned.

Missing Information: Specific acceptance criteria for blood pressure accuracy (e.g., mean difference and standard deviation between device and reference method) as defined by AAMI / ANSI SP10 were not detailed in the summary. The summary only states "PASS" for AAMI / ANSI SP10.

2. Sample Size Used for the Test Set and Data Provenance:

The document mentions "PERFORMANCE & CLINICAL TEST 3. AAMI / ANSI SP10," implying a clinical validation study was conducted. However, it does not provide details on the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective).

3. Number of Experts Used to Establish Ground Truth and Their Qualifications:

The document does not provide any information on the number of experts used or their qualifications for establishing ground truth, as is common in AI/ML device studies. This is expected since this device predates the widespread use of advanced AI in medical devices and its submission is based on traditional medical device validation. For blood pressure monitors, the "ground truth" is typically established by trained technicians following a standardized protocol using a reference auscultatory method.

4. Adjudication Method for the Test Set:

This information is not applicable or provided. For traditional blood pressure monitor validation per AAMI / ANSI SP10, the comparison is typically against a standardized reference method (e.g., mercury sphygmomanometer with trained observers), not expert adjudication of images or diagnoses.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

An MRMC study was not conducted or reported. This type of study is primarily relevant for AI devices that assist human readers in tasks like image interpretation, not for automated measurement devices like a blood pressure monitor.

6. Standalone (Algorithm Only) Performance Study:

A standalone study of the algorithm's performance was done in the sense that the device itself, the "CalHealth Finger Blood Pressure Monitor, MDMouse," was subjected to performance testing against established standards (AAMI/ANSI SP10). The device operates as a standalone system to measure blood pressure. The summary indicates that the device's "Oscillometric method" automatically senses pulse signals and calculates blood pressure. This implies the algorithm within the device was validated to perform these measurements.

7. Type of Ground Truth Used:

For blood pressure monitors, the ground truth is typically established by simultaneous measurements using a reference auscultatory method (e.g., using a mercury sphygmomanometer or an equivalent reference device) performed by trained observers. The AAMI / ANSI SP10 standard specifies the methodology for this.

8. Sample Size for the Training Set:

This information is not applicable or provided. Blood pressure monitors using the oscillometric method are typically based on well-established algorithms derived from physiological principles and extensive empirical data, not from machine learning models requiring a "training set" in the modern AI sense. The algorithms are usually pre-determined and validated against clinical data, rather than being "trained" iteratively.

9. How the Ground Truth for the Training Set Was Established:

This information is not applicable or provided for the same reasons as #8. The "ground truth" for developing such an algorithm would have been based on extensive physiological and clinical studies over many years by the broader scientific community, rather than a specific training set constructed for this particular device's development.

In summary, the 510(k) emphasizes compliance with recognized standards for safety and performance (AAMI/ANSI SP10) to demonstrate substantial equivalence. It does not provide the detailed breakdown of clinical study parameters (sample size, ground truth specifics, etc.) that would be expected in a pre-market submission for a novel AI/ML-based device.

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